Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System
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The purpose of this thesis is to evaluate the potential for recent deep policy- based reinforcement learning methods to improve on blood glucose control in type 1 diabetes.. Type
activities influenced their blood glucose levels, 2 participants (P05 and P11) clearly expressed their need for improvement of the feedback design so that it visually showed
Subjects and Methods: Thirty patients with insulin-regulated type 1 diabetes were equipped with a mobile phone application for 3–6 months, recording blood glucose, insulin,
Keywords: Type 1 diabetes, Mobile phones, Data-driven feedback, Self-measured blood glucose, Pattern
(Tronstad et al., 2017)) of SA and ECG sensor data and a global threshold could provide detection of hypoglycemia in people with diabetes with normal/adequate hormonal reactions
From the reconstruction-based method, PCA produced better description for all sample sizes, whereas K-means and SOM achieved comparable performance with sample size
For å sammenholde resultatene med nasjonale tall, beregnet vi gjennomsnittlig prevalens på samme måte og hentet data fra Medisinsk fødselsregister for type 1-diabetes, type
The Few Touch application is a mobile-phone-based self-management system for people with Type 2 diabetes mellitus (T2DM) de- veloped by involving patient-users in design
